Mental Health Status of Rural Female Left-Behind Middle School Students in Sichuan Province
Bibliographic record
Abstract
Objective: To investigate the mental health status of rural left-behind middle school students in Sichuan province, and set some requirements for family, school and society. Method: This paper used Middle School Student Mental Health Scale (MSSMHS) developed by Wang to investigate the mental health status of 690 female left-behind middle school students and analyzed the data by using SPSS 20.0. Results: 38% of the rural left-behind middle school students had mental health problems; there were significant differences in compulsion, crankiness and hostility between junior school students and high school students; there were significant differences in anxiety and learning stress between only children and non-only children; there were significant differences in different workplaces of parents and different time spent with parents. Conclusion：The mental health status of rural female left-behind middle school students is not optimistic, and family, school, society and government should take effective measures to improve the metal health status of rural left-behind middle school students.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".